Andrew J. Gentles

Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor

BackgroundRepbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases.ResultsWe describe the software tools RepbaseSubmitter and Censor, which are designed to facilitate updating and screening the content of Repbase. RepbaseSubmitter is a java-based interface for formatting and annotating Repbase entries. It eliminates many common formatting errors, and automates actions such as calculation of sequence lengths and composition, thus facilitating curation of Repbase sequences. In addition, it has several features for predicting protein coding regions in sequences; searching and including Pubmed references in Repbase entries; and searching the NCBI taxonomy database for correct inclusion of species information and taxonomic position. Censor is a tool to rapidly identify repetitive elements by comparison to known repeats. It uses WU-BLAST for speed and sensitivity, and can conduct DNA-DNA, DNA-protein, or translated DNA-translated DNA searches of genomic sequence. Defragmented output includes a map of repeats present in the query sequence, with the options to report masked query sequence(s), repeat sequences found in the query, and alignments.ConclusionCensor and RepbaseSubmitter are available as both web-based services and downloadable versions. They can be found at http://www.girinst.org/repbase/submission.html (RepbaseSubmitter) and http://www.girinst.org/censor/index.php (Censor).

Robust enumeration of cell subsets from tissue expression profiles

We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu/).

The prognostic landscape of genes and infiltrating immune cells across human cancers

Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing data sets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies. By using this resource, we identified a forkhead box MI (FOXM1) regulatory network as a major predictor of adverse outcomes, and we found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and facilitate the discovery of biomarkers and therapeutic targets.

Calreticulin Is the Dominant Pro-Phagocytic Signal on Multiple Human Cancers and Is Counterbalanced by CD47

Calreticulin-induced phagocytosis of cancer cells can be counterbalanced by CD47 expression. Eat Up! Immune cells constantly patrol the body on a search and destroy campaign against foreign invaders. Designed to detect differential molecular signals, cells of the immune system can distinguish healthy from infected tissue by the types of proteins produced: Infected cells, for example, often produce unfamiliar proteins, which then activate innate immune cells to “eat” (phagocytose) the infected ones. Cancer cells also carry aberrant cargo such as unfamiliar proteins or normal proteins at abnormal levels, yet these cells frequently escape immune attack because they express a “don’t eat me” signal, the cell surface protein CD47. Blocking this signal on a cancer cell makes them targets for phagocytosis, but surprisingly does not do the same for normal cells that express CD47. Chao et al. have now identified calreticulin as the “eat me” signal on cancer cells that leads to phagocytosis when the counterbalancing “don’t eat me” signal CD47 is blocked. Calreticulin is a pro-phagocytic molecule that is highly expressed on the surface of several types of human cancer cells, including acute myeloid and lymphoblastic leukemias, chronic myeloid leukemia, non-Hodgkin’s lymphoma, bladder cancer, glioblastoma, and ovarian cancer. However, calreticulin is expressed only at very low levels on normal cells. Chao et al. found a correlation between calreticulin and CD47 expression levels on cancer cells and showed that blocking the interaction between calreticulin and its ligand prevented phagocytosis initiated by blocking the “don’t eat me” signal CD47. Moreover, high calreticulin expression on cancer cells was a poor prognostic indicator in human patients with neuroblastoma, bladder cancer, and non-Hodgkin’s lymphoma. Therefore, a balance between calreticulin and CD47 expression in cancer cells may be a double-edged sword: In the absence of a CD47 blocker, this equilibrium may support tumor cell survival, but when CD47 function is inhibited, the presence of calreticulin tells immune cells to “eat up!” This information provides a key insight for the therapeutic development of CD47-inhibitory agents. Under normal physiological conditions, cellular homeostasis is partly regulated by a balance of pro- and anti-phagocytic signals. CD47, which prevents cancer cell phagocytosis by the innate immune system, is highly expressed on several human cancers including acute myeloid leukemia, non-Hodgkin’s lymphoma, and bladder cancer. Blocking CD47 with a monoclonal antibody results in phagocytosis of cancer cells and leads to in vivo tumor elimination, yet normal cells remain mostly unaffected. Thus, we postulated that cancer cells must also display a potent pro-phagocytic signal. Here, we identified calreticulin as a pro-phagocytic signal that was highly expressed on the surface of several human cancers, but was minimally expressed on most normal cells. Increased CD47 expression correlated with high amounts of calreticulin on cancer cells and was necessary for protection from calreticulin-mediated phagocytosis. Blocking the interaction of target cell calreticulin with its receptor, low-density lipoprotein receptor–related protein, on phagocytic cells prevented anti-CD47 antibody–mediated phagocytosis. Furthermore, increased calreticulin expression was an adverse prognostic factor in diverse tumors including neuroblastoma, bladder cancer, and non-Hodgkin’s lymphoma. These findings identify calreticulin as the dominant pro-phagocytic signal on several human cancers, provide an explanation for the selective targeting of tumor cells by anti-CD47 antibody, and highlight the balance between pro- and anti-phagocytic signals in the immune evasion of cancer.

Association of a Leukemic Stem Cell Gene Expression Signature With Clinical Outcomes in Acute Myeloid Leukemia

CONTEXT In many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immunodeficient mice, which indicate that human acute myeloid leukemia (AML) is driven by self-renewing leukemic stem cells (LSCs). This model has significant implications for the development of novel therapies, but its clinical relevance has yet to be determined. OBJECTIVE To identify an LSC gene expression signature and test its association with clinical outcomes in AML. DESIGN, SETTING, AND PATIENTS Retrospective study of global gene expression (microarray) profiles of LSC-enriched subpopulations from primary AML and normal patient samples, which were obtained at a US medical center between April 2005 and July 2007, and validation data sets of global transcriptional profiles of AML tumors from 4 independent cohorts (n = 1047). MAIN OUTCOME MEASURES Identification of genes discriminating LSC-enriched populations from other subpopulations in AML tumors; and association of LSC-specific genes with overall, event-free, and relapse-free survival and with therapeutic response. RESULTS Expression levels of 52 genes distinguished LSC-enriched populations from other subpopulations in cell-sorted AML samples. An LSC score summarizing expression of these genes in bulk primary AML tumor samples was associated with clinical outcomes in the 4 independent patient cohorts. High LSC scores were associated with worse overall, event-free, and relapse-free survival among patients with either normal karyotypes or chromosomal abnormalities. For the largest cohort of patients with normal karyotypes (n = 163), the LSC score was significantly associated with overall survival as a continuous variable (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.08-1.22; log-likelihood P <.001). The absolute risk of death by 3 years was 57% (95% CI, 43%-67%) for the low LSC score group compared with 78% (95% CI, 66%-86%) for the high LSC score group (HR, 1.9 [95% CI, 1.3-2.7]; log-rank P = .002). In another cohort with available data on event-free survival for 70 patients with normal karyotypes, the risk of an event by 3 years was 48% (95% CI, 27%-63%) in the low LSC score group vs 81% (95% CI, 60%-91%) in the high LSC score group (HR, 2.4 [95% CI, 1.3-4.5]; log-rank P = .006). In multivariate Cox regression including age, mutations in FLT3 and NPM1, and cytogenetic abnormalities, the HRs for LSC score in the 3 cohorts with data on all variables were 1.07 (95% CI, 1.01-1.13; P = .02), 1.10 (95% CI, 1.03-1.17; P = .005), and 1.17 (95% CI, 1.05-1.30; P = .005). CONCLUSION High expression of an LSC gene signature is independently associated with adverse outcomes in patients with AML.

Amino acid runs in eukaryotic proteomes and disease associations.

We present a comparative proteome analysis of the five complete eukaryotic genomes (human, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana), focusing on individual and multiple amino acid runs, charge and hydrophobic runs. We found that human proteins with multiple long runs are often associated with diseases; these include long glutamine runs that induce neurological disorders, various cancers, categories of leukemias (mostly involving chromosomal translocations), and an abundance of Ca2 + and K+ channel proteins. Many human proteins with multiple runs function in development and/or transcription regulation and are Drosophila homeotic homologs. A large number of these proteins are expressed in the nervous system. More than 80% of Drosophila proteins with multiple runs seem to function in transcription regulation. The most frequent amino acid runs in Drosophila sequences occur for glutamine, alanine, and serine, whereas human sequences highlight glutamate, proline, and leucine. The most frequent runs in yeast are of serine, glutamine, and acidic residues. Compared with the other eukaryotic proteomes, amino acid runs are significantly more abundant in the fly. This finding might be interpreted in terms of innate differences in DNA-replication processes, repair mechanisms, DNA-modification systems, and mutational biases. There are striking differences in amino acid runs for glutamine, asparagine, and leucine among the five proteomes.

Hierarchy in somatic mutations arising during genomic evolution and progression of follicular lymphoma.

Follicular lymphoma (FL) is currently incurable using conventional chemotherapy or immunotherapy regimes, compelling new strategies. Advances in high-throughput sequencing technologies that can reveal oncogenic pathways have stimulated interest in tailoring therapies toward actionable somatic mutations. However, for mutation-directed therapies to be most effective, the mutations must be uniformly present in evolved tumor cells as well as in the self-renewing tumor-cell precursors. Here, we show striking intratumoral clonal diversity within FL tumors in the representation of mutations in the majority of genes as revealed by whole exome sequencing of subpopulations. This diversity captures a clonal hierarchy, resolved using immunoglobulin somatic mutations and IGH-BCL2 translocations as a frame of reference and by comparing diagnosis and relapse tumor pairs, allowing us to distinguish early versus late genetic eventsduring lymphomagenesis. We provide evidence that IGH-BCL2 translocations and CREBBP mutations are early events, whereas MLL2 and TNFRSF14 mutations probably represent late events during disease evolution. These observations provide insight into which of the genetic lesions represent suitable candidates for targeted therapies.

Why are human G-protein-coupled receptors predominantly intronless?

We thank H. Bourne (UCSF), A.M. Campbell (Stanford), S.R. Coughlin (UCSF), J. Jurka (Genetic Information Research Institute), B.K. Kobilka (Stanford), M.A. Krasnow (Stanford), G. Miklos (Neurosciences Research Institute, La Jolla) and L. Stryer (Stanford) for valuable discussions.

Mutations in early follicular lymphoma progenitors are associated with suppressed antigen presentation

Significance Follicular lymphoma (FL) is a disease characterized by multiple relapses that are linked by a common progenitor bearing only a subset of the mutations found within the tumor that presents clinically. Inability to cure this disease may therefore be linked to the failure of current therapies to clear these early tumor-propagating clones. Here we further define the genetic hallmarks of this disease and model the steps in evolution through phylogenetic analysis of serial tumor biopsies. This identified CREBBP mutations as early events in genome evolution that are enriched within tumor cell progenitors and provided evidence that these mutations act by allowing immune evasion. This highlights CREBBP mutations as an attractive therapeutic target in FL and provides insight into their pathogenic mechanism. Follicular lymphoma (FL) is incurable with conventional therapies and has a clinical course typified by multiple relapses after therapy. These tumors are genetically characterized by B-cell leukemia/lymphoma 2 (BCL2) translocation and mutation of genes involved in chromatin modification. By analyzing purified tumor cells, we identified additional novel recurrently mutated genes and confirmed mutations of one or more chromatin modifier genes within 96% of FL tumors and two or more in 76% of tumors. We defined the hierarchy of somatic mutations arising during tumor evolution by analyzing the phylogenetic relationship of somatic mutations across the coding genomes of 59 sequentially acquired biopsies from 22 patients. Among all somatically mutated genes, CREBBP mutations were most significantly enriched within the earliest inferable progenitor. These mutations were associated with a signature of decreased antigen presentation characterized by reduced transcript and protein abundance of MHC class II on tumor B cells, in line with the role of CREBBP in promoting class II transactivator (CIITA)-dependent transcriptional activation of these genes. CREBBP mutant B cells stimulated less proliferation of T cells in vitro compared with wild-type B cells from the same tumor. Transcriptional signatures of tumor-infiltrating T cells were indicative of reduced proliferation, and this corresponded to decreased frequencies of tumor-infiltrating CD4 helper T cells and CD8 memory cytotoxic T cells. These observations therefore implicate CREBBP mutation as an early event in FL evolution that contributes to immune evasion via decreased antigen presentation.

A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates

We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure, this method produces clinically meaningful estimators in a variety of settings. It can be useful for practicing personalized medicine: determining from a large set of biomarkers, the subset of patients that can potentially benefit from a treatment. We apply the method to both simulated datasets and real trial data. The modified covariates idea can be used for other purposes, for example, large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable. Supplementary materials for this article are available online.